Optimization of Boring Process Parameters By Using Taguchi Method

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1 Optimization of Boring Process Parameters By Using Taguchi Method ISSN: 8-8 Vol. Issue 8, August - 4 Mayuresh P Vaishnav*, *(Research Scholar Post graduate Student, Mechanical Engineering Department, Government College of Engineering, Aurangabad,Maharashtra,45) S A Sonawane** **(Asst. Professor, Mechanical Engineering, Department, Government College of Engineering, Aurangabad,Maharashtra,45) Dr. BabasahebAmbedkarMarathwada University Aurangabad, India Abstract : - In order to produce any product with desired quality by machining, proper selection of parameter is essential surface an indicator of surface quality is one of the prime customer requirement for machined parts. In this paper Taguchi parameter optimization methodology is applied to optimize cutting parameter as speed, feed and coolant flow for mild steel SAE54 using regression analysis method. The surface roughness were selected as the quality targets. The result analysis show that feed rate and cutting speed have present significant contribution on the surface roughness and coolant flow rate have less significant contribution on surface roughness. INTRODUCTION : Metal based industry are focused to increase productivity and quality of the machined parts. For these purpose all aspects of every process need to be monitored. Certain desired parameter of a machined parts are chosen and checked against desired degree of a quality. Surface finish is one of these important parameter in a manufacturing. It directly affects performing efficiency of a mechanical parts as well as their production cost. The ratio between cost and quality of a products n each production stage has t be monitored and immediate corrective action have to be taken in case of a deviation from a desired trend. BORING :For internal machining,boring is a precision operation. It increases whole diameter and also it gives desired degree of a surface roughness provided that parameters affecting are maintained under control conditions as observed in experimental analysis. This process used after drilling or cast. Boring is a unit process in manufacturing as a mass reduction step, used for enlarging and accurately sized existing hole by means of a single point of a cutting tool with multiple cutting edges Boring is used to achieve greater accuracy of the diameter of the hole and can be used to a cut tapered hole. Boring is done with the conjunction with turning, facing or other machined operation. Because of the limitation on tooling design imposed by the fact the work piece mostly surrounded the tool,boring is inherently somewhat more challenging than turning. Boring Can be viewed as the internal diameter counterpart to turning,which cuts external diameter. SURFACE ROUGHNESS AND MEASUREMENT Surface roughness of a machined product could affect several of the product s functional attributes, such as contact causing surface friction, wearing, light reflection, heat transmission, ability of distributing and holding a lubricant, coating, and resisting fatigue. There are several ways to describe surface rough- ness. One of them is average roughness which is often quoted as Ra symbol. Ra is defined as the arithmetic value of the departure of the profile from the centerline along sampling length as shown in Fig.. It can be expressed by the following mathematical relationships. Ra = L l ǀY x ǀ dx(l) where Ra=the arithmetic average deviation from the mean line, and Y =the ordinate of the profile curve. There are many methods of measuring surface roughness, such as using specimen blocks by eye or fingertip, microscopes, stylus type instruments, profile tracing instruments, etc. The tools measuring surface roughness with probes, measure, and control in appropriate length and circumferences. The probe comes in and out holes while traveling on the surface. The probe is made up of diamond nip which very high in cost. LITERATURE REVIEW ) Show-shynlin (9) investigated the optimization of 66T6 CNC boring process using the Taguchi method and grey relation analysis. the surface properties of a roughness average roughness and maximum roughness as well as the roundness were selected as to quality targets. Analysis of variance (ANOVA) is also used to analyze the influence of the cutting parameter during machining. The result related that the feed rate is the most influence factor on the average roughness and maximum roughness and the cutting speed is the most influential factor to the roundness. [ ] ) Adel H.Suhail et.al []() conducted experimental study to optimize the cutting parameter using two IJERTVIS86

2 ISSN: 8-8 Vol. Issue 8, August - 4 performance measure work piece, surface temperature and surface roughness. He has used carbon steel AISI and its dimension were 5mm long with 5 mm dia. Optimal cutting parameter for each performance were obtained using Taguchi techniques. The orthogonal array, signal to noise ratio and ANOVA were employed to study the performance characteristics in operation. The experimental result showed that the work piece surface temperature can be sensed and used effectively as an indicator to control the cutting performance and improves the optimization process. ) Harriman Singh sodhi () Investigated cutting parameters for surface roughness of a mild steel in boring process using Taguchi method. He investigated that the influence of the three most important machining parameter of depth of cut, feed rate and the cutting speed on surface roughness during turning of a mild steel by using carbide tool of.6 mm of a noise radius. ANOVA is used to analyze the influence of the machining parameter of the surface roughness. Results shows that the cutting speed and feed rate have present significant contribution on the surface roughness and depth of cut have less significant contribution on surface roughness. 4) GauravVhora () investigated that the analysis and optimization of a boring process parameter by using Taguchi method. In investigation boring parameters for a CNC turning center such as speed, feed experiment,dept of cut is done on a aluminum to achieve the highest possible material removal rate and at that same time minimum surface roughness by using the Taguchi method. The objective of the study was to identify the performance characteristics and select process parameter to be evaluate and to determine the no. of parameters level for the process and possible interaction between the process parameter. Experimental Medium carbon low alloy steel ASI54is nothing but the mild steel. It was used as work piece material (Hardness,5-59 HRC).Chromium (Cr),Manganese (Mn) and Silicon (Si) alloyed materials offers a very good polish ability and this material we are using to make a gear shifting fork. Material composition of work piece is as follows : C,.4; Mn,.5; Si,.5; Cr,.; Al,.5; Cu,.5% by wt. Table : Chemical composition of work-piece component C Mn Si Cr Al Cu HRC TAGUCHI METHOD Taguchi method based design of experiment has been used to study effect of three machining parameters like speed, feed, coolant flow on one important parameter like surface roughness. for selecting appropriate orthogonal arrays, degree of freedom of array is calculated. There are eight degree of freedom owing to three machining input parameters, so Taguchi based L9 arrays is selected. Accordingly,9 experiment were carried out the study the effect of machining input.parameters. Each experimentwas repeated three times in order to reduce experimental errors. In all tests, roughness was measured using surface roughness tester made by MITITOYO model no.sj4.the roughness tester having measuring force 5mN-4mN and Diamond tip 5µm stylus having accuracy ±.µm.the probe comes in and out holes while traveling on the surface. The probe is made up of diamond nip which very high in cost EXPERIMENTAL CONDITIONS A series of experiments were carried out on Hyundai WIA F5DI (VMC) (Sanjeev Auto). From OVAT analysis four input controlling parameters selected having three levels. Details of parameters and their levels used shown in the table: Table. Machining parameters and their levels Parameter Level Level Level Speed (rpm) 9 Feed (mm/min) Coolant flow (lit/min) EXPERIMENTAL PROCEDURE High performance HYNDAI WIA f 5D CNC Milling machine (working space, X, Y and Z movements being mm) variable spindle speeds, optimum 8 rpm; main spindle power,4. kw.having table size 5mm was employed to perform experiments for boring rough bar (Material, cemented carbide K grade; cylinder shank helix angle and chafer 9 ).The tool bar having overall length (Ɩ) 4 mm;,flute length (Ɩ) 85mm; cutting diameter (d), 6.4mm and shank diameter (d), 5.5mm. S/N ratio for Ra was calculated IJERTVIS86 8

3 ISSN: 8-8 Vol. Issue 8, August - 4 Table : Experimental design matrix of L9 Orthogonal Array by Minitab 4 Exp No A Speed (rpm) B Feed (mm/min) C Coolant Flow Rate (Lit/min) RESULTS AND ANALYSIS A table is got after actual experimentation, showing Ra values and S/N ratios for each trials. Table is given below: Table 4 Response table for Ra SPEED FEED COOLANT FLOW RATE Ra S/N Ratio Table 5 Analysis of Variance for Means Source DF Seq SS Speed. Feed. 9 Coolant Flow Error.. Total Adj SS Adj MS S =.48 R-Sq = 99.56% R-Sq(adj) = 98.% F P In table 4 Analysis of Variances had been done ( ANOVA) and it reflects that the value P is less than.5 in all three parametric sources.therefore it is clear that all three parameters have significant effect on the surface roughness while boring. Table 6 Response Table for Means (smaller is better) for Ra Level Speed Feed Coolant Flow Delta Rank Main Effects Plot (data means) for Means SPEED FEED Mean of Means.8. 9 CF Fig.main effect plot for Ra It is clear form main effect plot as shown in figure that surface roughness is increasing with increasing IJERTVIS86 9

4 ISSN: 8-8 Vol. Issue 8, August - 4 inspeed from rpm to rpm but it decreases with the change in further increases in speed from 9 to rpm. Similarly in the case of feed rate we will get the minimum surface roughness at 9mm/revolution. Minimum value of surface roughness lies at liter/min. Table Analysis of variance for S/N ratio Source D Seq Adj Adj F P F SS SS MS Speed Feed Coolant Flow Residua l Error From main effect plot in figure 6.It has been shown that the value of a S/N ratio is maximum at speed of rpm and minimum at rpm.. further it has been shown that the value of S/N ratio is increasing initially but it decreases further with the increasing in feed rate. Taguchi statics for Ra Firstly data has checked for its normality by probability plot (see figure). As data points are distributed all along the normal line and having negligible outliers, so data can be concluded as normally distributed. The second plot doesn't show any trend while plotting residual verses fitted value of data which implies Taguchi model chosen is well fitted with given data set. Third plot is frequency histogram showing data distribution and at last residue verses order plot highlights the random data points which signifies non-significance of experimental order as far as first response (Ra) is concerned. Total Mean of SNratios S =.894 R-Sq = 99.% R-Sq(adj) = 9.49% Table 8 Response Table for S/N ratio Level Speed Feed Coolant Flow Delta Rank - - Main Effects Plot (data means) for SN ratios SPEED 9 CF 9 FEED Percent Sr no. Frequency Normal Probability Plot of the s -.. Predicted Ra mean. Histogram of the s Plots for RA MIN Fig. plot for Ra mean CONFORMATION TEST Table 9 Conformation Test Exp. Trial Exp. Trial.8. Fitted Value Exp. Ra mean % Error s Versus the Fitted Values Observation Order 8.4 s Versus the Order of the Data 9 4 Signal-to-noise: Smaller is better 6 Fig. Main effets plot for S/N ratios IJERTVIS86

5 ISSN: 8-8 Vol. Issue 8, August - 4 CONCLUSION REFERENCES This study discussed an application of the Taguchi method of optimizing the cutting parameters of boring operation. from this research, following conclusion could be reached with a fair amount of confidence. Regardless of the category of the quality characteristics, the lower the better for surface roughness the lowest feed rate (F=9 mm/min),the highest cutting speed ( S= rpm ) and the lowest coolant flow ( C= lit/min) lead to the optimal surface roughness value. for solving machining optimization problems, various conventional techniques had been used so far, but they are not robust and have problems when applied to the boring process, which involves a numbers of variables and constrains. To overcome the above problems, Taguchi method is used in this work. since Taguchi method is experimental method it is realistic in nature. According to this study the prime factor affecting surface finish is feed and after that cutting speed and coolant flow. ) Show-Shyn Lin, Ming-TsanChaung, Jeoung-Lian Wen, and Yung- Kaung Yang ''Optimization of 66T6 CNC Boring Process Using the Taguchi Method and Grey Relation Analysis' The Open Industrial and Manufacturing Engineering, Journal,9,, 4- ) Adeel H. Suhail, N. Ismail, S.V.Wong and N.A. Abdul Jalil "Optimization of Cutting Parameters Based on Surface Roughness and Assistance ofworkpiece Surface Temperature in turning process'' American Journal of Engineering and Applied Sciences (),pp -8, ) Harimansinghsodhi, DhirajPrakashDhiman, Ramesh Kumar Gupta, Raminder Singh Bhatia " Investigation of Cutting Parameters For Surface Roughness of Mild Steel In Boring Process Using Taguchi Method" International Journal OF Applied Engineering Research, ISSN Vol. No.9 () 4) GauravVohra, Palwinder Singh, Harimansinghsodhi '' Analysis and Optimization of Boring Parameters By Using Taguchi Method'' International Journal of Computer Science and Communication Engineering, ISSN 9-8, NCRAET- 5) Parvesh Kumar Rajvanshi, Dr. R.M. Belokar ''Improving the Process Capability of a Boring Operation by Application of Statistical Techniques' International Journal of Scientific and Engineering Research Volume, ISSN -558, 5 May-. 6) M G Mehrabi, G O Neal, B-K Min, Z.Pasek and Y.Koren ''Improving Machining Accuracy in Precision Line Boring'' Journal of Intelligent Manufacturing,, 9-89, ) Rang-Tai Yang, Hsin-Te-Ligo, Yung-Kaung Yang, Show-Shyn Lin '' Modeling and Optimization in Precise Boring Processes For Aluminum Alloy 66T6 Component ''International Journal of Precision Engineering and Manufacturing, Vol, No., PP -6, Jan IJERTVIS86